Abstract
The conceptual design of a reactive separation process for the hydration of ethylene to ethanol requires reliable vapor–liquid equilibrium (VLE) data for the ternary system ethylene+water+ethanol. Due to the paucity of experimental data points in the VLE phase diagrams that have been reported for that system, molecular simulation looks appealing in order to predict such data. In this work, the Gibbs-ensemble Monte Carlo (GEMC) method was used to calculate the VLE of the pure components (ethylene, water, and ethanol), the binary subsystems (ethylene+water, ethylene+ethanol, and ethanol+water), and the ternary system (ethylene+water+ethanol). A set of previously validated Lennard-Jones plus point-charge potential models were chosen for the pure components, and the validity of these models was corroborated from the good agreement of the GEMC simulation results for the vapor pressure and the VLE phase diagrams of those components with respect to calculations carried out by means of the most accurate (reference) multiparameter equations of state currently available for ethylene, water, and ethanol. These potential models were found to be capable of predicting the available VLE phase diagrams of the binary subsystems: ethylene+water at 200 and 250°C, ethylene+ethanol at 150, 170, 190, 200, and 220°C, and ethanol+water at 200, 250, 275, and 300°C. Molecular simulation predictions for the VLE phase diagrams of the ternary system at 200°C and pressures of 30, 40, 50, 60, 80, and 100atm, were found to be in very good agreement with predictions previously made by use of a thermodynamic model that combines the Peng–Robinson–Stryjek–Vera equation of state, the Wong–Sandler mixing rules, and the UNIQUAC activity coefficient model. The agreement between the predictions of these two independent approaches gives confidence for the subsequent use of molecular simulation to predict the combined phase and chemical equilibrium of the ternary system and check the validity of predictions previously made by means of the thermodynamic model.
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